Call for Submissions: Special Issue on Taxonomies, Ontologies, and Knowledge Graphs: Advancing Information Integrity, Knowledge Accuracy, and Ethical AI

Taxonomies, ontologies, knowledge graphs, and related knowledge organization systems and semantic models are central to how information is organized, represented, connected, retrieved, interpreted, and reused. Across libraries, archives, research infrastructures, digital platforms, enterprise information environments, and artificial intelligence systems, these structures support discovery, decision-making, interoperability, and the integrity of knowledge.

Their role is becoming more consequential as information science addresses developments in knowledge representation and semantic modeling; knowledge graphs, linked data, and semantic information integration; semantic approaches to information retrieval and discovery; and the rapidly expanding intersection of taxonomies, ontologies and knowledge graphs with generative AI and large language models. These developments create new opportunities for contextualization, explainability, and trustworthy information systems while raising important questions about knowledge quality, provenance, bias, inclusion, governance, and responsible AI.

In this special issue of Information Matters, we invite contributions from across the information science research community, including doctoral and early-career researchers and established scholars, as well as librarians, library and information science researchers, educators, and information professionals. We welcome concise, accessible essays, case studies, research perspectives, and practical frameworks that examine current research questions, methodological developments, empirical findings, research-in-progress, and research-informed professional practice. Contributions should be engaging and accessible to a broad information community.

Potential Questions to Be Addressed

• • • Information Integrity and Knowledge Quality: How do taxonomies, ontologies, knowledge graphs, and related knowledge organization systems support accurate, reliable, and trustworthy information ecosystems? How can their quality, interoperability, sustainability, and fitness for purpose be evaluated?
    • Representation, Bias, and Inclusion: How do choices in classification, terminology, modeling, and relationship design shape what knowledge is visible or marginalized? How can researchers and practitioners identify and mitigate bias, representational harms, cultural assumptions, and epistemic gaps while supporting diverse, local, Indigenous, and domain-specific perspectives?
    • Knowledge Governance: What governance, maintenance, and sustainability practices help taxonomies, ontologies, and knowledge graphs remain current, transparent, adaptable, and responsive to evolving language, research, communities, and organizational needs? How should semantic drift, concept evolution, and terminology change be managed over time?
    • Transparency and Provenance: How can metadata, evidence, source attribution, authority, uncertainty, and semantic relationships improve traceability, accountability, and trust? What roles can linked data and knowledge graphs play in semantic interoperability and information integration across libraries, research infrastructures, open science, digital scholarship, and enterprise environments?
    • Ethics in Knowledge Organization: What ethical principles should guide the development and application of taxonomies, ontologies, knowledge graphs, and semantic models? How can knowledge organization support inclusive representation, responsible information retrieval and discovery, and accountable human oversight?
    • Supporting Trustworthy AI: How are large language models and generative AI changing ontology and knowledge graph creation, enrichment, alignment, evaluation, and maintenance? How can these resources support retrieval-augmented generation, grounding, validation, explainability, and information accuracy, and how should they interact with other approaches?
    • Emerging Challenges and Opportunities: How are advances in AI, knowledge management, information retrieval, semantic search, linked data, and semantic technologies reshaping research and professional practice? What emerging methods and research problems should shape doctoral and early-career work, and what can researchers, librarians, taxonomists, knowledge managers, and other information professionals learn from one another?

Why This Special Issue?

Questions of trust, accuracy, bias, representation, retrieval, transparency, and accountability increasingly sit at the center of information research and practice. Taxonomies, ontologies, and knowledge graphs have long provided foundations for organizing and connecting knowledge, but their importance is growing as information environments become more complex and organizations adopt AI at scale. This special issue connects foundational and emerging research in knowledge organization with semantic technologies, information retrieval and discovery, information integrity, and responsible AI. It offers a space for researchers, librarians, and information professionals to share empirical findings, emerging methods, practical approaches, and critical perspectives on building more accurate, inclusive, ethical, and trustworthy information systems.

Author Instructions

All proposals should be submitted directly through the Information Matters’ platform, following the author’s instructions. Authors are encouraged to include illustrations with their texts. Submitted pieces should ideally be 1,000 words, aimed at a general audience, and should not contain traditional academic citations or reference lists. Instead, authors may embed links where appropriate.

Before submitting, please create an account at https://informationmatters.org. Once registered, create a post that will serve as your submission to the Special Issue. When submitting your article, make sure to designate “SI Taxonomies” as a tag. The texts will be published simultaneously on SSRN in a citable format with a DOI, volume, and issue number, and will be indexed in several publication databases.

For your writing reference, you can find recently published articles here: https://informationmatters.org/si-nformation-privilege-and-the-cultures-of-scholarly-communication/ 

Timeline

Submission deadline: November 30, 2026
Full issue publication: December 2026
Publication/indexing through SSRN: December 2026

Decisions and publication via the Information Matters website: typically within two weeks of submission

Questions

For questions about the special issue, please contact: Marisa Hughes MHughes@apa.org

Editors

Guest Editor:
Marisa Hughes, Taxonomist
APA Publishing, American Psychological Association, Washington, DC